Measuring object positions in space is a routine, but important activity in industry, and is generally called industrial dimensional metrology. The present invention is directed to large scale industrial dimensional metrology, which concerns measurements over a volume of a few cubic meters to several 100 meters cubed. There is always a need for higher accuracy, higher resolution, acquisition of spatial coordinates with lower cost measurement systems and equipment, in less acquisition time, with less processing power and complexity, and with less equipment setup and calibration time, although various application spaces have different weightings for these requirements.
One thrust to achieve these goals is multi-modal acquisition, which holds the promise of leveraging advantages of different measurement systems. For example, if two lower cost measurement systems, such as a higher accuracy, slower, point-wise measurement system (like laser trackers and optically tracked coordinate measurement machines), and faster, wide field of view, acquisition systems (such as photogrammetric systems) can together acquire in less time, large scene spatial arrangement information from an object space with as good or better accuracy and precision than slower, but usually higher cost systems (like 3D laser scanners, and LIDAR systems), a larger market for the coordinated (multi-modal) lower cost measurement systems may open up.
Furthermore, some LIDAR and 3D laser scanners present views of the object space that are unnaturally devoid of surface colour or texture information and it may be desirable to augment such views with photographic information. So integration of data from different measurement systems is desirable for several reasons.
Integration of multimodal information is essential to newer and more advanced techniques (e.g. photogrammetric processes), which rely on “point cloud” data. There are growing uses for verifying integration and registration of separate 3D image point clouds.
Unfortunately there are some problems with aligning data produced by disparate measurement systems. Each measurement system typically has a respective coordinate system, and mapping the object space representations of multiple systems is uncertain, and leads to greater uncertainties at distance from the origins of the two systems. If one can acquire a same target in each of a plurality of object space representations, the mapping uncertainty can be reduced greatly, and systematic, low complexity, algorithms known in the art can be used to accomplish the mapping.
Even if multimodal measurement systems are not used, targets that are capable of reliable, efficient spatial coordinate acquisition for a number of measurement systems reduce a number of targets required for field work or deployment, and provide greater flexibility of redesigning measurement systems after deployment.
As an example of the knowledge in the field of targets for non-contact dimensional metrology, Applicant offers: The Journal of the CMSC The Publication For 3D Measurement Technology, Vol. 9, No. 2, Autumn 2014. The target claimed and used to demonstrate the present invention was incidentally shown on the coverpage of the issue. It has a crossed-rectangle shape (sometimes referred to as a bowtie shape). No description of any part of these targets was provided in the paper authored by Applicant contained in the issue. The images in the paper itself were essentially 2D and therefore indistinguishable from well-known prior art 2D contrast targets. The image clearly highlights spherical targets and their applications for non-contact dimensional metrology. The image is included in the journal as an eye catching and busy illustration of a metrology system. The inclusion of the image was incidental, and is clearly deemphasized in the image as the spherical targets used are all identified by various identifiers and connections.
Applicant notes that the field of this Journal, and particularly Applicant's paper, on pp. 4-10 of the issue, is fundamental metrology as opposed to industrial or applied metrology: The purposes relate to comparisons of measurement systems, and standards for tracing confidence in measures to the standards, as opposed to measurements of industrial articles, and the equipment therefor.
In Applicant's paper (Target selection starting near bottom of left col. p. 8), it is noted that there are 3 classes of target: contrast (C), spherical (S), and plane (P). FIG. 4 shows illustrations of each: including contrast type targets a crossed-rectangular target (C-NRC), and a concentric circular target (C-HDS); three spherical targets (S-ATS, S-INO, and S-Men); and a single plane (P-1) and a 3 plane (P-3). See also FIG. 2 for another example of a single plane target (a), and a target with an end that is of a crossed rectangular (bowtie) cross-section shape, for easy identification of a centre of the target. The paper states, regarding FIG. 4:                The ideal target would be one in which derivation of the target center is highly repeatable for all scanning systems and would be measurable by the RI (Reference Instrument). The final decision of target type was not based solely on repeatability, but this metric could be used to eliminate targets that perform poorly. For example, spheres were favored even before testing was initiated because they can be imaged from any position or orientation. As a result, these experiments were used to determine how well spheres performed compared to other target surfaces such as contrast targets and planes. Spheres and planes also have the benefit of being easily measured using the SMR of a laser tracker, something not possible with most contrast targets.A section entitled Estimating target geometric centers on p. 7 offers some insight into why the “derivation of the target center” is important, and how the person of ordinary skill would be led to the conclusion that spheres are ideal candidates for targets.        
This disclosure does not address integration of 2D and 3D imaging systems, but rather disparages contrast type targets, which are reliably and efficiently used in 2D methods and in photogrammetric applications. An important feature is lost in discarding the contrast type targets that was not expressed in the paper: it is particularly easy to reliably determine the centre of contrast targets of the crossed rectangular form, using 2D techniques, and 3D approaches based on corrected 2D techniques.
Basis Software Inc. (Redmond Wash.) has developed and marketed a flat contrast target designed to be mounted to a nest for a SMR. The target has a conventional, contrast, crossed rectangular (bowtie) pattern on one side and a hemisphere mounted on the other side. The hemisphere is designed to be received in a nest for an industry-standard 1.5″ retroreflector (SMR). Such a target makes the nest useful for 2D and 3D approaches. Thus, a point identified with the nest by a 3D measurement system (such as a laser tracker) with an SMR mounted to the nest, and a point associated with the nest by a 2D measurement system (a laser scanner, lidar, or photogrammetric system) using the flat contrast target, can be reliably associated by the fixity of the nest.
Reportedly the centre of the contrast target and the 3D measurement's centre are within 50 μm of deviation from each other. Unfortunately aligning the hemisphere with respect to the centre of the flat contrast target leads to errors in such a system, and increases complexity and costs of producing of these targets. Furthermore, it would be preferable if the same surface can be used both for contact with an SMR and for 2D contrast imaging, to avoid having to replace targets in a scene between 2D and 3D imaging, and to reduce equipment for dimensional metrology.
Accordingly there is a need for a technique for improving integration of targets for different imaging modalities, and particularly to targets for which a derivation of the centre is repeatable.